Triple

T3929580
Position Surface form Disambiguated ID Type / Status
Subject Charade E93363 entity
Predicate producer P490 FINISHED
Object Stanley Donen E45045 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Stanley Donen | Statement: [Charade, producer, Stanley Donen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stanley Donen
Context triple: [Charade, producer, Stanley Donen]
  • A. Stanley Donen chosen
    Stanley Donen was an American film director and choreographer best known for co-directing classic Hollywood musicals such as "Singin' in the Rain" and "On the Town."
  • B. Vincente Minnelli
    Vincente Minnelli was an American film director best known for his visually distinctive and influential Hollywood musicals, including classics like "An American in Paris" and "Gigi."
  • C. Herbert Ross
    Herbert Ross was an American choreographer and film director known for his work on Broadway and in Hollywood, including acclaimed movies such as "The Goodbye Girl" and "Steel Magnolias."
  • D. Blake Edwards
    Blake Edwards was an American filmmaker best known for his stylish comedies and classics like the Pink Panther series and Breakfast at Tiffany’s.
  • E. Michael Curtiz
    Michael Curtiz was a Hungarian-American film director best known for helming classic Hollywood films such as "Casablanca."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69aed96bfa1081908f7b30f2c647dee6 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeeda65b708190b24cd715915aec1d completed March 9, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b53387775881909479f4e1fcecdaca completed March 14, 2026, 10:08 a.m.
Created at: March 9, 2026, 3:23 p.m.